{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using matplotlib backend: MacOSX\n",
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/vonw/anaconda3/envs/pangeo/lib/python3.6/site-packages/IPython/core/magics/pylab.py:160: UserWarning: pylab import has clobbered these variables: ['figsize', 'figure']\n",
      "`%matplotlib` prevents importing * from pylab and numpy\n",
      "  \"\\n`%matplotlib` prevents importing * from pylab and numpy\"\n"
     ]
    }
   ],
   "source": [
    "%pylab\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "trp = pd.read_table('trp.dat', sep='\\s+', names=['layer', 'altitude', 'pressure', 'temperature', 'dew_point', 'density', 'h2o', 'co2', 'o3', 'n2o', 'co', 'ch4', 'o2'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>layer</th>\n",
       "      <th>altitude</th>\n",
       "      <th>pressure</th>\n",
       "      <th>temperature</th>\n",
       "      <th>dew_point</th>\n",
       "      <th>density</th>\n",
       "      <th>h2o</th>\n",
       "      <th>co2</th>\n",
       "      <th>o3</th>\n",
       "      <th>n2o</th>\n",
       "      <th>co</th>\n",
       "      <th>ch4</th>\n",
       "      <th>o2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1013.000</td>\n",
       "      <td>299.7</td>\n",
       "      <td>260.94</td>\n",
       "      <td>2.448000e+19</td>\n",
       "      <td>25930.000</td>\n",
       "      <td>330.0</td>\n",
       "      <td>0.02869</td>\n",
       "      <td>0.320000</td>\n",
       "      <td>0.15000</td>\n",
       "      <td>1.7000</td>\n",
       "      <td>209000.0</td>\n",
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       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>904.000</td>\n",
       "      <td>293.7</td>\n",
       "      <td>237.88</td>\n",
       "      <td>2.229000e+19</td>\n",
       "      <td>19500.000</td>\n",
       "      <td>330.1</td>\n",
       "      <td>0.03151</td>\n",
       "      <td>0.320100</td>\n",
       "      <td>0.14510</td>\n",
       "      <td>1.7010</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>805.000</td>\n",
       "      <td>287.7</td>\n",
       "      <td>216.40</td>\n",
       "      <td>2.027000e+19</td>\n",
       "      <td>15350.000</td>\n",
       "      <td>330.1</td>\n",
       "      <td>0.03344</td>\n",
       "      <td>0.320100</td>\n",
       "      <td>0.14000</td>\n",
       "      <td>1.7010</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3.0</td>\n",
       "      <td>715.000</td>\n",
       "      <td>283.7</td>\n",
       "      <td>195.12</td>\n",
       "      <td>1.825000e+19</td>\n",
       "      <td>8607.000</td>\n",
       "      <td>330.3</td>\n",
       "      <td>0.03507</td>\n",
       "      <td>0.320300</td>\n",
       "      <td>0.13500</td>\n",
       "      <td>1.7010</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>633.000</td>\n",
       "      <td>277.0</td>\n",
       "      <td>177.04</td>\n",
       "      <td>1.655000e+19</td>\n",
       "      <td>4443.000</td>\n",
       "      <td>330.2</td>\n",
       "      <td>0.03563</td>\n",
       "      <td>0.320200</td>\n",
       "      <td>0.13130</td>\n",
       "      <td>1.7010</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>5.0</td>\n",
       "      <td>559.000</td>\n",
       "      <td>270.3</td>\n",
       "      <td>160.25</td>\n",
       "      <td>1.498000e+19</td>\n",
       "      <td>3348.000</td>\n",
       "      <td>330.2</td>\n",
       "      <td>0.03770</td>\n",
       "      <td>0.320200</td>\n",
       "      <td>0.13040</td>\n",
       "      <td>1.7010</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>6.0</td>\n",
       "      <td>492.000</td>\n",
       "      <td>263.6</td>\n",
       "      <td>144.65</td>\n",
       "      <td>1.352000e+19</td>\n",
       "      <td>2103.000</td>\n",
       "      <td>330.3</td>\n",
       "      <td>0.03992</td>\n",
       "      <td>0.320300</td>\n",
       "      <td>0.12890</td>\n",
       "      <td>1.7010</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>7.0</td>\n",
       "      <td>432.000</td>\n",
       "      <td>257.0</td>\n",
       "      <td>130.29</td>\n",
       "      <td>1.217000e+19</td>\n",
       "      <td>1290.000</td>\n",
       "      <td>330.1</td>\n",
       "      <td>0.04225</td>\n",
       "      <td>0.320100</td>\n",
       "      <td>0.12480</td>\n",
       "      <td>1.7000</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>8.0</td>\n",
       "      <td>378.000</td>\n",
       "      <td>250.3</td>\n",
       "      <td>117.07</td>\n",
       "      <td>1.094000e+19</td>\n",
       "      <td>764.500</td>\n",
       "      <td>330.4</td>\n",
       "      <td>0.04476</td>\n",
       "      <td>0.320300</td>\n",
       "      <td>0.11860</td>\n",
       "      <td>1.6990</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>9.0</td>\n",
       "      <td>329.000</td>\n",
       "      <td>243.6</td>\n",
       "      <td>104.70</td>\n",
       "      <td>9.782000e+18</td>\n",
       "      <td>410.100</td>\n",
       "      <td>330.2</td>\n",
       "      <td>0.05003</td>\n",
       "      <td>0.319700</td>\n",
       "      <td>0.10950</td>\n",
       "      <td>1.6940</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>10.0</td>\n",
       "      <td>286.000</td>\n",
       "      <td>237.0</td>\n",
       "      <td>93.55</td>\n",
       "      <td>8.740000e+18</td>\n",
       "      <td>191.300</td>\n",
       "      <td>330.2</td>\n",
       "      <td>0.05599</td>\n",
       "      <td>0.318100</td>\n",
       "      <td>0.09969</td>\n",
       "      <td>1.6860</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>11.0</td>\n",
       "      <td>247.000</td>\n",
       "      <td>230.1</td>\n",
       "      <td>83.22</td>\n",
       "      <td>7.775000e+18</td>\n",
       "      <td>73.110</td>\n",
       "      <td>330.2</td>\n",
       "      <td>0.06617</td>\n",
       "      <td>0.314200</td>\n",
       "      <td>0.08970</td>\n",
       "      <td>1.6760</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>13</td>\n",
       "      <td>12.0</td>\n",
       "      <td>213.000</td>\n",
       "      <td>223.6</td>\n",
       "      <td>73.85</td>\n",
       "      <td>6.900000e+18</td>\n",
       "      <td>29.070</td>\n",
       "      <td>330.2</td>\n",
       "      <td>0.07820</td>\n",
       "      <td>0.309700</td>\n",
       "      <td>0.07819</td>\n",
       "      <td>1.6630</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "      <td>13.0</td>\n",
       "      <td>182.000</td>\n",
       "      <td>217.0</td>\n",
       "      <td>65.02</td>\n",
       "      <td>6.075000e+18</td>\n",
       "      <td>9.907</td>\n",
       "      <td>330.2</td>\n",
       "      <td>0.09296</td>\n",
       "      <td>0.305000</td>\n",
       "      <td>0.06378</td>\n",
       "      <td>1.6460</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>15</td>\n",
       "      <td>14.0</td>\n",
       "      <td>156.000</td>\n",
       "      <td>210.3</td>\n",
       "      <td>57.51</td>\n",
       "      <td>5.373000e+18</td>\n",
       "      <td>6.225</td>\n",
       "      <td>330.3</td>\n",
       "      <td>0.10510</td>\n",
       "      <td>0.300100</td>\n",
       "      <td>0.05029</td>\n",
       "      <td>1.6270</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "      <td>15.0</td>\n",
       "      <td>132.000</td>\n",
       "      <td>203.7</td>\n",
       "      <td>50.24</td>\n",
       "      <td>4.694000e+18</td>\n",
       "      <td>4.003</td>\n",
       "      <td>330.2</td>\n",
       "      <td>0.12570</td>\n",
       "      <td>0.294600</td>\n",
       "      <td>0.03944</td>\n",
       "      <td>1.6060</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>16.0</td>\n",
       "      <td>111.000</td>\n",
       "      <td>197.0</td>\n",
       "      <td>43.68</td>\n",
       "      <td>4.081000e+18</td>\n",
       "      <td>3.002</td>\n",
       "      <td>330.2</td>\n",
       "      <td>0.14450</td>\n",
       "      <td>0.287900</td>\n",
       "      <td>0.03071</td>\n",
       "      <td>1.5830</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>18</td>\n",
       "      <td>17.0</td>\n",
       "      <td>93.700</td>\n",
       "      <td>194.8</td>\n",
       "      <td>37.29</td>\n",
       "      <td>3.484000e+18</td>\n",
       "      <td>2.902</td>\n",
       "      <td>330.2</td>\n",
       "      <td>0.25010</td>\n",
       "      <td>0.278500</td>\n",
       "      <td>0.02490</td>\n",
       "      <td>1.5540</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>19</td>\n",
       "      <td>18.0</td>\n",
       "      <td>78.900</td>\n",
       "      <td>198.8</td>\n",
       "      <td>30.77</td>\n",
       "      <td>2.875000e+18</td>\n",
       "      <td>2.752</td>\n",
       "      <td>330.3</td>\n",
       "      <td>0.50040</td>\n",
       "      <td>0.267300</td>\n",
       "      <td>0.01968</td>\n",
       "      <td>1.5220</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>20</td>\n",
       "      <td>19.0</td>\n",
       "      <td>66.600</td>\n",
       "      <td>202.7</td>\n",
       "      <td>25.47</td>\n",
       "      <td>2.380000e+18</td>\n",
       "      <td>2.601</td>\n",
       "      <td>330.2</td>\n",
       "      <td>0.95050</td>\n",
       "      <td>0.252800</td>\n",
       "      <td>0.01550</td>\n",
       "      <td>1.4810</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>21</td>\n",
       "      <td>20.0</td>\n",
       "      <td>56.500</td>\n",
       "      <td>206.7</td>\n",
       "      <td>21.19</td>\n",
       "      <td>1.980000e+18</td>\n",
       "      <td>2.602</td>\n",
       "      <td>330.2</td>\n",
       "      <td>1.40100</td>\n",
       "      <td>0.236600</td>\n",
       "      <td>0.01332</td>\n",
       "      <td>1.4250</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>22</td>\n",
       "      <td>21.0</td>\n",
       "      <td>48.000</td>\n",
       "      <td>210.7</td>\n",
       "      <td>17.66</td>\n",
       "      <td>1.650000e+18</td>\n",
       "      <td>2.652</td>\n",
       "      <td>330.2</td>\n",
       "      <td>1.80100</td>\n",
       "      <td>0.219500</td>\n",
       "      <td>0.01233</td>\n",
       "      <td>1.3560</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>23</td>\n",
       "      <td>22.0</td>\n",
       "      <td>40.900</td>\n",
       "      <td>214.6</td>\n",
       "      <td>14.78</td>\n",
       "      <td>1.380000e+18</td>\n",
       "      <td>2.801</td>\n",
       "      <td>330.1</td>\n",
       "      <td>2.40100</td>\n",
       "      <td>0.205200</td>\n",
       "      <td>0.01233</td>\n",
       "      <td>1.2730</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>24</td>\n",
       "      <td>23.0</td>\n",
       "      <td>35.000</td>\n",
       "      <td>217.0</td>\n",
       "      <td>12.50</td>\n",
       "      <td>1.168000e+18</td>\n",
       "      <td>2.902</td>\n",
       "      <td>330.2</td>\n",
       "      <td>3.40200</td>\n",
       "      <td>0.196800</td>\n",
       "      <td>0.01308</td>\n",
       "      <td>1.1920</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>25</td>\n",
       "      <td>24.0</td>\n",
       "      <td>30.000</td>\n",
       "      <td>219.2</td>\n",
       "      <td>10.61</td>\n",
       "      <td>9.913000e+17</td>\n",
       "      <td>3.202</td>\n",
       "      <td>330.2</td>\n",
       "      <td>4.30300</td>\n",
       "      <td>0.187600</td>\n",
       "      <td>0.01401</td>\n",
       "      <td>1.1190</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.700</td>\n",
       "      <td>221.4</td>\n",
       "      <td>9.00</td>\n",
       "      <td>8.408000e+17</td>\n",
       "      <td>3.252</td>\n",
       "      <td>330.2</td>\n",
       "      <td>5.40300</td>\n",
       "      <td>0.175700</td>\n",
       "      <td>0.01522</td>\n",
       "      <td>1.0560</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26</td>\n",
       "      <td>27</td>\n",
       "      <td>27.5</td>\n",
       "      <td>17.630</td>\n",
       "      <td>227.0</td>\n",
       "      <td>6.02</td>\n",
       "      <td>5.625000e+17</td>\n",
       "      <td>3.602</td>\n",
       "      <td>330.2</td>\n",
       "      <td>7.80500</td>\n",
       "      <td>0.158900</td>\n",
       "      <td>0.01723</td>\n",
       "      <td>0.9877</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>27</td>\n",
       "      <td>28</td>\n",
       "      <td>30.0</td>\n",
       "      <td>12.200</td>\n",
       "      <td>232.3</td>\n",
       "      <td>4.07</td>\n",
       "      <td>3.804000e+17</td>\n",
       "      <td>4.003</td>\n",
       "      <td>330.3</td>\n",
       "      <td>9.30800</td>\n",
       "      <td>0.141700</td>\n",
       "      <td>0.01997</td>\n",
       "      <td>0.9143</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>28</td>\n",
       "      <td>29</td>\n",
       "      <td>32.5</td>\n",
       "      <td>8.520</td>\n",
       "      <td>237.7</td>\n",
       "      <td>2.78</td>\n",
       "      <td>2.596000e+17</td>\n",
       "      <td>4.303</td>\n",
       "      <td>330.2</td>\n",
       "      <td>9.85700</td>\n",
       "      <td>0.116600</td>\n",
       "      <td>0.02268</td>\n",
       "      <td>0.8306</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29</td>\n",
       "      <td>30</td>\n",
       "      <td>35.0</td>\n",
       "      <td>6.000</td>\n",
       "      <td>243.1</td>\n",
       "      <td>1.91</td>\n",
       "      <td>1.788000e+17</td>\n",
       "      <td>4.603</td>\n",
       "      <td>330.2</td>\n",
       "      <td>9.70700</td>\n",
       "      <td>0.092820</td>\n",
       "      <td>0.02489</td>\n",
       "      <td>0.7466</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>30</td>\n",
       "      <td>31</td>\n",
       "      <td>37.5</td>\n",
       "      <td>4.260</td>\n",
       "      <td>248.5</td>\n",
       "      <td>1.33</td>\n",
       "      <td>1.242000e+17</td>\n",
       "      <td>4.905</td>\n",
       "      <td>330.4</td>\n",
       "      <td>8.81000</td>\n",
       "      <td>0.067000</td>\n",
       "      <td>0.02741</td>\n",
       "      <td>0.6625</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31</td>\n",
       "      <td>32</td>\n",
       "      <td>40.0</td>\n",
       "      <td>3.050</td>\n",
       "      <td>254.0</td>\n",
       "      <td>0.93</td>\n",
       "      <td>8.697000e+16</td>\n",
       "      <td>5.203</td>\n",
       "      <td>330.2</td>\n",
       "      <td>7.50500</td>\n",
       "      <td>0.045160</td>\n",
       "      <td>0.03100</td>\n",
       "      <td>0.5642</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>32</td>\n",
       "      <td>33</td>\n",
       "      <td>42.5</td>\n",
       "      <td>2.200</td>\n",
       "      <td>259.4</td>\n",
       "      <td>0.66</td>\n",
       "      <td>6.143000e+16</td>\n",
       "      <td>5.504</td>\n",
       "      <td>330.2</td>\n",
       "      <td>5.90400</td>\n",
       "      <td>0.027530</td>\n",
       "      <td>0.03512</td>\n",
       "      <td>0.4617</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>33</td>\n",
       "      <td>34</td>\n",
       "      <td>45.0</td>\n",
       "      <td>1.590</td>\n",
       "      <td>264.8</td>\n",
       "      <td>0.47</td>\n",
       "      <td>4.349000e+16</td>\n",
       "      <td>5.704</td>\n",
       "      <td>330.2</td>\n",
       "      <td>4.50300</td>\n",
       "      <td>0.015920</td>\n",
       "      <td>0.03990</td>\n",
       "      <td>0.3633</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>34</td>\n",
       "      <td>35</td>\n",
       "      <td>47.5</td>\n",
       "      <td>1.160</td>\n",
       "      <td>269.6</td>\n",
       "      <td>0.33</td>\n",
       "      <td>3.116000e+16</td>\n",
       "      <td>5.905</td>\n",
       "      <td>330.3</td>\n",
       "      <td>3.45300</td>\n",
       "      <td>0.009386</td>\n",
       "      <td>0.04486</td>\n",
       "      <td>0.2775</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>35</td>\n",
       "      <td>36</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.854</td>\n",
       "      <td>270.2</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2.289000e+16</td>\n",
       "      <td>6.005</td>\n",
       "      <td>330.3</td>\n",
       "      <td>2.80200</td>\n",
       "      <td>0.004756</td>\n",
       "      <td>0.05096</td>\n",
       "      <td>0.2102</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>36</td>\n",
       "      <td>37</td>\n",
       "      <td>55.0</td>\n",
       "      <td>0.456</td>\n",
       "      <td>263.4</td>\n",
       "      <td>0.13</td>\n",
       "      <td>1.254000e+16</td>\n",
       "      <td>6.005</td>\n",
       "      <td>330.3</td>\n",
       "      <td>1.80200</td>\n",
       "      <td>0.003003</td>\n",
       "      <td>0.05990</td>\n",
       "      <td>0.1652</td>\n",
       "      <td>209200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>37</td>\n",
       "      <td>38</td>\n",
       "      <td>60.0</td>\n",
       "      <td>0.239</td>\n",
       "      <td>253.1</td>\n",
       "      <td>0.07</td>\n",
       "      <td>6.839000e+15</td>\n",
       "      <td>6.004</td>\n",
       "      <td>330.2</td>\n",
       "      <td>1.10100</td>\n",
       "      <td>0.002066</td>\n",
       "      <td>0.06965</td>\n",
       "      <td>0.1501</td>\n",
       "      <td>209100.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    layer  altitude  pressure  temperature  dew_point       density  \\\n",
       "0       1       0.0  1013.000        299.7     260.94  2.448000e+19   \n",
       "1       2       1.0   904.000        293.7     237.88  2.229000e+19   \n",
       "2       3       2.0   805.000        287.7     216.40  2.027000e+19   \n",
       "3       4       3.0   715.000        283.7     195.12  1.825000e+19   \n",
       "4       5       4.0   633.000        277.0     177.04  1.655000e+19   \n",
       "5       6       5.0   559.000        270.3     160.25  1.498000e+19   \n",
       "6       7       6.0   492.000        263.6     144.65  1.352000e+19   \n",
       "7       8       7.0   432.000        257.0     130.29  1.217000e+19   \n",
       "8       9       8.0   378.000        250.3     117.07  1.094000e+19   \n",
       "9      10       9.0   329.000        243.6     104.70  9.782000e+18   \n",
       "10     11      10.0   286.000        237.0      93.55  8.740000e+18   \n",
       "11     12      11.0   247.000        230.1      83.22  7.775000e+18   \n",
       "12     13      12.0   213.000        223.6      73.85  6.900000e+18   \n",
       "13     14      13.0   182.000        217.0      65.02  6.075000e+18   \n",
       "14     15      14.0   156.000        210.3      57.51  5.373000e+18   \n",
       "15     16      15.0   132.000        203.7      50.24  4.694000e+18   \n",
       "16     17      16.0   111.000        197.0      43.68  4.081000e+18   \n",
       "17     18      17.0    93.700        194.8      37.29  3.484000e+18   \n",
       "18     19      18.0    78.900        198.8      30.77  2.875000e+18   \n",
       "19     20      19.0    66.600        202.7      25.47  2.380000e+18   \n",
       "20     21      20.0    56.500        206.7      21.19  1.980000e+18   \n",
       "21     22      21.0    48.000        210.7      17.66  1.650000e+18   \n",
       "22     23      22.0    40.900        214.6      14.78  1.380000e+18   \n",
       "23     24      23.0    35.000        217.0      12.50  1.168000e+18   \n",
       "24     25      24.0    30.000        219.2      10.61  9.913000e+17   \n",
       "25     26      25.0    25.700        221.4       9.00  8.408000e+17   \n",
       "26     27      27.5    17.630        227.0       6.02  5.625000e+17   \n",
       "27     28      30.0    12.200        232.3       4.07  3.804000e+17   \n",
       "28     29      32.5     8.520        237.7       2.78  2.596000e+17   \n",
       "29     30      35.0     6.000        243.1       1.91  1.788000e+17   \n",
       "30     31      37.5     4.260        248.5       1.33  1.242000e+17   \n",
       "31     32      40.0     3.050        254.0       0.93  8.697000e+16   \n",
       "32     33      42.5     2.200        259.4       0.66  6.143000e+16   \n",
       "33     34      45.0     1.590        264.8       0.47  4.349000e+16   \n",
       "34     35      47.5     1.160        269.6       0.33  3.116000e+16   \n",
       "35     36      50.0     0.854        270.2       0.25  2.289000e+16   \n",
       "36     37      55.0     0.456        263.4       0.13  1.254000e+16   \n",
       "37     38      60.0     0.239        253.1       0.07  6.839000e+15   \n",
       "\n",
       "          h2o    co2       o3       n2o       co     ch4        o2  \n",
       "0   25930.000  330.0  0.02869  0.320000  0.15000  1.7000  209000.0  \n",
       "1   19500.000  330.1  0.03151  0.320100  0.14510  1.7010  209100.0  \n",
       "2   15350.000  330.1  0.03344  0.320100  0.14000  1.7010  209100.0  \n",
       "3    8607.000  330.3  0.03507  0.320300  0.13500  1.7010  209200.0  \n",
       "4    4443.000  330.2  0.03563  0.320200  0.13130  1.7010  209100.0  \n",
       "5    3348.000  330.2  0.03770  0.320200  0.13040  1.7010  209200.0  \n",
       "6    2103.000  330.3  0.03992  0.320300  0.12890  1.7010  209200.0  \n",
       "7    1290.000  330.1  0.04225  0.320100  0.12480  1.7000  209100.0  \n",
       "8     764.500  330.4  0.04476  0.320300  0.11860  1.6990  209200.0  \n",
       "9     410.100  330.2  0.05003  0.319700  0.10950  1.6940  209100.0  \n",
       "10    191.300  330.2  0.05599  0.318100  0.09969  1.6860  209200.0  \n",
       "11     73.110  330.2  0.06617  0.314200  0.08970  1.6760  209100.0  \n",
       "12     29.070  330.2  0.07820  0.309700  0.07819  1.6630  209100.0  \n",
       "13      9.907  330.2  0.09296  0.305000  0.06378  1.6460  209100.0  \n",
       "14      6.225  330.3  0.10510  0.300100  0.05029  1.6270  209200.0  \n",
       "15      4.003  330.2  0.12570  0.294600  0.03944  1.6060  209200.0  \n",
       "16      3.002  330.2  0.14450  0.287900  0.03071  1.5830  209200.0  \n",
       "17      2.902  330.2  0.25010  0.278500  0.02490  1.5540  209100.0  \n",
       "18      2.752  330.3  0.50040  0.267300  0.01968  1.5220  209200.0  \n",
       "19      2.601  330.2  0.95050  0.252800  0.01550  1.4810  209100.0  \n",
       "20      2.602  330.2  1.40100  0.236600  0.01332  1.4250  209100.0  \n",
       "21      2.652  330.2  1.80100  0.219500  0.01233  1.3560  209100.0  \n",
       "22      2.801  330.1  2.40100  0.205200  0.01233  1.2730  209100.0  \n",
       "23      2.902  330.2  3.40200  0.196800  0.01308  1.1920  209100.0  \n",
       "24      3.202  330.2  4.30300  0.187600  0.01401  1.1190  209200.0  \n",
       "25      3.252  330.2  5.40300  0.175700  0.01522  1.0560  209100.0  \n",
       "26      3.602  330.2  7.80500  0.158900  0.01723  0.9877  209100.0  \n",
       "27      4.003  330.3  9.30800  0.141700  0.01997  0.9143  209200.0  \n",
       "28      4.303  330.2  9.85700  0.116600  0.02268  0.8306  209200.0  \n",
       "29      4.603  330.2  9.70700  0.092820  0.02489  0.7466  209200.0  \n",
       "30      4.905  330.4  8.81000  0.067000  0.02741  0.6625  209200.0  \n",
       "31      5.203  330.2  7.50500  0.045160  0.03100  0.5642  209100.0  \n",
       "32      5.504  330.2  5.90400  0.027530  0.03512  0.4617  209100.0  \n",
       "33      5.704  330.2  4.50300  0.015920  0.03990  0.3633  209100.0  \n",
       "34      5.905  330.3  3.45300  0.009386  0.04486  0.2775  209200.0  \n",
       "35      6.005  330.3  2.80200  0.004756  0.05096  0.2102  209200.0  \n",
       "36      6.005  330.3  1.80200  0.003003  0.05990  0.1652  209200.0  \n",
       "37      6.004  330.2  1.10100  0.002066  0.06965  0.1501  209100.0  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Tropical Standard Atmosphere')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,12))\n",
    "plt.semilogy(trp.temperature-273.15, trp.pressure)\n",
    "plt.gca().invert_yaxis()\n",
    "xlabel('Temperature (C)')\n",
    "ylabel('Pressure (mb)')\n",
    "title('Tropical Standard Atmosphere')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Tropical Standard Atmosphere')"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,12))\n",
    "plt.semilogy(trp.h2o/1e6*100, trp.pressure)\n",
    "plt.gca().invert_yaxis()\n",
    "xlabel('Water Vapor (%)')\n",
    "ylabel('Pressure (mb)')\n",
    "title('Tropical Standard Atmosphere')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Tropical Standard Atmosphere')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,12))\n",
    "plt.semilogy((trp.co2.values).astype(int), trp.pressure)\n",
    "plt.gca().invert_yaxis()\n",
    "xlabel('Carbon Dioxide (ppm)')\n",
    "ylabel('Pressure (mb)')\n",
    "title('Tropical Standard Atmosphere')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
